Not long ago, the thought of Artificial intelligence (AI) products becoming mainstream seemed far off. Fast forward to the widespread adoption of ChatGPT, Gemini, and other large-scale apps, and it’s easy to see that the world has changed drastically. AI isn’t just the future anymore – it’s the present, and every business is hopping on the bandwagon. From chatbots streamlining customer service to algorithms predicting market trends, AI is reshaping how businesses operate.

Every application, web or non-web-based, has to deal with data. Even though there are static websites, where data is somehow embedded, most sites and applications rely on dynamic data stored somewhere and somehow. What testing can you do around data handling? Can you use exploratory testing to uncover problems related to data? What type of problems? In this article, you’ll get some guidelines for your exploratory testing sessions around data.

Building and consuming Application Programming Interfaces (APIs) has become an essential skill for developers. APIs are the glue that enables seamless integration and interaction between different software systems, including those that leverage AI. As the demand for artificial intelligence (AI) grows, the monetization of AI APIs has emerged as a critical concern for businesses looking to capitalize on their technological investments. Almost all AI functionality that companies build is exposed as an API.

As one of the most popular programming languages, Java has stood the test of time. The versatile and powerful language has a vast ecosystem and offers numerous advantages and opportunities, whether you’re a beginner or an experienced developer. This post covers Java benefits, various use cases, and why monitoring your Java applications is crucial to application success.

Snowflake Cortex Search, a fully managed search service for documents and other unstructured data, is now in public preview. With Cortex Search, organizations can effortlessly deploy retrieval-augmented generation (RAG) applications with Snowflake, powering use cases like customer service, financial research and sales chatbots.

As someone who’s been closely following the evolution of software testing, this year saw the shifts in methodologies and processes. One of the most significant findings is the strong adoption of Agile and DevOps methodologies, reshaping how testing is integrated into the software development lifecycle.

Choosing the right software development vendor is essential to ensure your project succeeds. A suitable partner can deliver high-quality solutions, manage projects efficiently, and align with your specific requirements. Moreover, they will contribute significantly to your digital transformation efforts by implementing the latest technologies and best practices. So, where should you look for the best software development vendors?

Processes are the foundation of your organization. They lay the groundwork for how your business operates, from product development and customer service to procurement and financial operations—and everything in between. Even work that isn’t formally defined in a process is likely a part of one. If you’ve ever tried to map or document a business process, you’ve probably learned that there’s no straightforward way to get it done.